GA_PSO_Optimization

在MATLAB程序中利用FDATOOL工具得到系数，然后由此十进制系数生成CSD码(In the MATLAB program by using FDATOOL tools coefficient, then the resulting decimal CSD code coefficients generated)

gmcalab 快速广义的形态分量分析算法，用于图像修复，稀疏分解、降噪等，用途广泛。从mca主页下载的(gmcalab fast generalized morphological component analysis algorithm for image restoration, sparse decomposition, noise reduction, and versatile. Mca downloaded from the home page)

java与matlab编程的例题。想要做类似工程项目的人员可以参考哦。(java and matlab programming examples. Want to do similar projects can reference Oh.)

通过该功能，可以处理图像中的很多问题，是图像分析处理的主要工具。(image)

Modulation and demodulation ASK. At the beginning, we create the digital signa (1 and 0), after we do the modulation, add noise and demodulation. At the end we do the reconstruction of the signal.

说明：  我们知道，小波变换的一级分解过程是，原始信号分别进行低通、高通滤波，再分别进行二元下抽样，就得到低频、高频（也称为平均、细节）两部分系数；而多级分解则是对上一级分解得到的低频系数再进行小波分解，是一个递归过程。以下是一维小波分解的程序. (We know that a wavelet transform decomposition process is that the original signal were low-pass, high pass filter, and then carried out under the binary sample, we obtained low-frequency, high-frequency (also known as the average, details) coefficient of two parts and Multi-level decomposition is a decomposition of the previous low-frequency coefficients to be further wavelet decomposition is a recursive process. Following is a one-dimensional wavelet decomposition process.)

实现MIMO－OFDM功率、信道、比特等资源自适应分配的注水算法。(MIMO-OFDM realize the power, channel, bit-allocation of resources such as water injection adaptive algorithm.)

说明：  这是matlab的根轨迹程序代码，很好很好的代码(This is the root locus matlab code, very good very good code)

this matlab source code is for begining

此为模式识别中Parzen窗法估计概率密度函数。 全部程序流程如下： 1、读取FAMALE.TXT文件把身高或体重给数组，并求x1的样本数N1和窗宽、体宽； 2、读取MALE.TXT文件把身高或体重给数组，并求x2的样本数N2和窗宽、体宽； 3、读取Test2.txt文件把对应的身高或体重给数组A并求A的样本数M； 4、利用Parzen窗法估计概率密度函数判别男女性别； 5、对本判别的错误率进行统计。 (This is the pattern recognition Parzen window method to estimate the probability density function . All program flow is as follows : 1 , read FAMALE.TXT file to height or weight to the array, and find the number of samples x1 N1 and window width , body width 2 , read MALE.TXT file to height or weight to the array, and find the number of samples x2 N2 and window width , body width 3 , read Test2.txt file to the corresponding height or weight requirements for the array A and A is the number of samples M 4 , the use of Parzen window method to estimate the probability density function of gender discrimination 5 , determine the error rate of the statistics . )